Monitoring of Ionospheric Anomalies Using GNSS Observations to Detect Earthquake Precursors

The study of the Earth's ionosphere is a topic that has increased in relevance over the past few decades. The ability to predict the ionosphere's behavior, as well as to mitigate the effects of its rapid changes, is a matter of primary importance in satellite communications, positioning, and navigation applications at present. Ionosphere perturbations can be produced by geomagnetic storms correlated with the solar activity or by earthquakes, volcanic activities, and so on. The monitoring of space weather is achieved through analyzing the Vertical Total Electron Content (VTEC) and its anomalies by means of time series, maps, and other derived parameters. In this study, we outline a strategy to estimate the VTEC in real-time, its rate of change, and the corresponding Signal-to-Noise Ratio (SNR) based on dual-frequency GNSS Doppler observations. We describe how to compute these parameters from GNSS data for a regional network using Adjusted Spherical Harmonic Analysis (ASHA) applied to a local model. The proposed method was tested to study ionospheric anomalies for two seismic events: the 2015 Nepal and 2023 Turkey earthquakes. In both cases, anomalies were detected in the maps of the differential VTEC (DTEC), differential VTEC rate, and SNR of the VTEC produced close to the earthquake zone. The robustness of the results is strongly related to the availability of a dense Ionosphere Pierce Point (IPP) cloud on the ionospheric layer and surrounding the studied area. At present, the distribution of Continuously Operating Reference Stations (CORSs) around the world is insufficiently dense and homogeneous in certain regions (e.g., the oceans). Robustness can be improved by increasing the number of CORSs and developing new models involving measurements over ocean surfaces.